Towards workload shift detection and prediction for autonomic databases
Marc Holze, Norbert Ritter · 2007
Due to the complexity of industry-scale database systems, the total cost of ownership for these systems is no longer dominated by hardware and software, but by administration expenses. Autonomic databases intend to reduce these costs by providing self-management features. Existing approaches towards this goal are supportive advisors for the database administrator and feedback control loops for online monitoring, analysis and re-configuration. But while advisors are too resource-consuming for continuous operation, feedback control loops suffer from overreaction, oscillation and interference.